BESC 3010 Exam 2 Questions and Answers | Latest Version | 2024/2025 | Rated A+
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Course
BESC 3010
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BESC 3010
BESC 3010 Exam 2 Questions and
Answers | Latest Version | 2024/2025 |
Rated A+
What is a population parameter, and how is it different from a sample statistic?
A population parameter is a value that describes a characteristic of an entire population,
while a sample statistic describes a ch...
BESC 3010 Exam 2 Questions and
Answers | Latest Version | 2024/2025 |
Rated A+
What is a population parameter, and how is it different from a sample statistic?
✔✔A population parameter is a value that describes a characteristic of an entire population,
while a sample statistic describes a characteristic of a sample from that population.
Why is random sampling important in statistics?
✔✔Random sampling is important because it ensures each member of the population has an
equal chance of being selected, which helps create a representative sample and reduces bias.
What does the standard deviation tell us about a data set?
✔✔Standard deviation tells us how spread out the values in a data set are around the mean,
indicating the amount of variation or dispersion in the data.
Explain the concept of margin of error in a confidence interval.
✔✔The margin of error represents the range above and below a sample statistic, within which
the true population parameter is expected to fall, providing a measure of the precision of the
estimate.
1
,What is the purpose of using a t-test in statistics?
✔✔A t-test is used to determine if there is a significant difference between the means of two
groups, helping researchers evaluate whether any observed differences are due to chance.
How does a paired t-test differ from an independent t-test?
✔✔A paired t-test compares two related samples, such as pre- and post-test scores for the same
group, while an independent t-test compares the means of two separate groups.
What is the purpose of an F-test in ANOVA?
✔✔The F-test in ANOVA is used to compare the variances between groups to determine if there
are statistically significant differences among the group means.
When is it appropriate to use a one-tailed test?
✔✔A one-tailed test is used when the research hypothesis predicts a specific direction of the
effect, such as an increase or decrease, rather than simply any difference.
What does the p-value measure in hypothesis testing?
2
,✔✔The p-value measures the probability of obtaining the observed results, or more extreme
results, assuming the null hypothesis is true. A low p-value suggests that the observed effect is
statistically significant.
What is the null hypothesis in a hypothesis test?
✔✔The null hypothesis is a statement that there is no effect or no difference in the population,
serving as the default or starting assumption in hypothesis testing.
What is statistical significance, and how is it determined?
✔✔Statistical significance indicates that the observed result is unlikely to be due to chance
alone, typically determined by a p-value less than a chosen significance level, such as 0.05.
What does it mean if the confidence interval for a difference in means includes zero?
✔✔If the confidence interval for a difference in means includes zero, it suggests that there may
be no significant difference between the groups, as zero represents no effect.
How does increasing the sample size affect the standard error?
✔✔Increasing the sample size decreases the standard error, making the sample statistic a more
accurate estimate of the population parameter.
3
, What is the difference between descriptive and inferential statistics?
✔✔Descriptive statistics summarize and describe data, while inferential statistics use data from a
sample to make predictions or inferences about a population.
What is a Type I error in hypothesis testing?
✔✔A Type I error occurs when the null hypothesis is incorrectly rejected, meaning a researcher
concludes there is an effect when there actually isn’t one.
What is a Type II error in hypothesis testing?
✔✔A Type II error occurs when the null hypothesis is incorrectly accepted, meaning a
researcher fails to detect an effect that actually exists.
Explain the purpose of using a chi-square test.
✔✔A chi-square test is used to evaluate relationships between categorical variables, assessing
whether observed frequencies differ from expected frequencies under the null hypothesis.
What does a strong positive correlation mean?
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